Abstract

Topic: Moose management and monitoring


Assessing Moose Population Demographics in New Hampshire through Camera Trap Analysis

Sarah Nicole Richard1, Henry Jones2, Lily M. Hall1, Mairi K. P. Poisson1, Andrew R. Butler1, Remington J. Moll1

  1. Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH 03824, USA
  2. New Hampshire Fish and Game Department, Lancaster, NH 03256 USA

BACKGROUND: Large-bodied ungulates hold significant ecological, economic, and cultural value. Ecologically, they influence nutrient cycling, seed dispersal, and forest composition, while economically and culturally, they contribute to recreation and wildlife viewing. Moose (Alces alces), the largest ungulate in North America, are iconic in New Hampshire, USA, where they support local economies through hunting and tourism. However, moose populations in New England have declined over the past two decades due to environmental and biological factors, including winter tick (Dermacentor albipictus) infestations, which have reduced New Hampshire’s moose population by ~45%. OBJECTIVES: Understanding moose population dynamics through key parameters such as adult sex ratios and productivity (cow-calf ratios) is critical for effective management and conservation. This study utilizes a network of camera traps across New Hampshire to estimate these demographic parameters. METHODS: In 2022 and 2023, we collected over 70,000 moose images with several instances of twins from 138 camera sites. We applied a Random Encounter and Staying Time model to estimate sex-specific densities and cow-calf ratios. PRELIMINARY RESULTS: We detected a density of 0.20 per km2 in bulls and a density of 0.27 per km2 in cows in 2022. Our findings aim to inform management strategies by providing precise estimates of sex ratios and productivity, offering insights into the impacts of environmental pressures, such as winter ticks, on moose demographics. Additionally, this study highlights the utility of camera traps as a valuable tool for monitoring ungulate populations. Camera traps provide a cost-effective and minimally invasive method for collecting data on moose populations compared to traditional aerial surveys, which are costly, weather-dependent, and prone to sightability bias. Broader implications include advancing demographic monitoring techniques for moose and other large-bodied ungulates, ultimately supporting data-driven wildlife management efforts. This approach is particularly valuable in landscapes where traditional survey methods are infeasible, reinforcing the role of innovative methodologies in addressing conservation challenges.